Efficacy of the World Health Organization Analgesic Ladder to Treat Pain in End-Stage Renal Disease
Bibliographic record
Abstract
Pain is the one of the most common symptoms experienced by patients with ESRD; it impairs their quality of life and is undertreated. Most pain clinicians believe that the pain management approach of the World Health Organization (WHO) three-step analgesic ladder is applicable to the treatment of patients with ESRD, but this approach has not been validated for them. A cohort of 45 hemodialysis patients were assessed for type and severity of pain using the Short-Form McGill Pain Questionnaire and then treated during a 4-wk period according to the WHO analgesic ladder. Mean age was 65 +/- 12.5 yr, and 22 (49%) patients had diabetic nephropathy as the cause of ESRD. Initial pain was rated severe by 34 (76%) patients. There was no difference in initial pain rating by gender, age, race, or type of pain. Forty percent of patients reported nociceptive pain, 31% neuropathic, and 29% both. Adequate analgesia was achieved in 43 (96%) of 45 patients. The mean pain score decreased from 7.8 +/- 1.2 to 1.6 +/- 1.3 (P < 0.001). Patients who were 65 yr and older had higher posttreatment scores than those who were younger than 65 (2.1 +/- 1.4 versus 0.94 +/- 0.93; P = 0.002) and more medication adverse effects. It is concluded that the use of the WHO three-step analgesic ladder leads to effective pain relief in hemodialysis patients. Older patients will need more careful pain management to achieve the same results as younger patients. Further studies are needed to confirm these results in a larger, more diverse dialysis population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".